Modeling the Market Dynamics from a Behavioral Perspective

Psychological studies on decision-making under uncertainty have shown that investors have systematic errors and behavioral biases in decision-making. Thus, market prices are more determined by psychological factors rather than the fundamental variables. In addition, standard asset pricing models based on rational expectations and homogeneity have problems cannot satisfactorily explain the dynamics and volatile nature of financial markets. So an important challenge of the financial theory in recent years is to construct models which have more consistencies with as many financial stylized facts that cannot be explained by traditional models. In this sense, the present study use Agent-based computational approach and more specifically Artificial Stock Market to modeling the market dynamics from a behavioral perspective. The purpose of this study is to point out a possibility that behavioral bias, specially anchoring feature of investors explains most number of financial stylized facts and plays an important role in price formations of financial markets. The results capture great kurtosis and asymmetry of return distribution. Moreover, by using agent-based simulations, the paper also provides a better representation of price dynamics in the financial market.